Investigating the consequences of accidentally grading CoT during RL

·LessWrong··

This is an unofficial automated linkpost. Monitoring our models’ chains of thought (CoT) has proven to be an effective way to detect and track model misalignment, both during RL training and deployment. While CoT monitoring has been useful for safety, we and many others in the industry believe CoT monitorability could be fragile. We would like to preserve and leverage CoT monitorability for as long as possible, and we recently introduced a suite of evaluations designed to measure it. Directly gr...

Read full article →

Related Articles

Devices with GrapheneOS support should be available in 2027
exceptione · Hacker News · 6h ago
Moderna reports first positive Phase 3 for mRNA neoantigen therapy in melanoma
heydenberk · Hacker News · 4h ago
Field measurements of neighborhood-scale air temperature impacts of data centers
cwwc · Hacker News · 1d ago
Solo – a .so loader for static Linux binaries
zX41ZdbW · Hacker News · 18h ago
The Mojo language (by Modular, now Qualcomm) is now open-source
flaburgan · Hacker News · 10h ago